7 resultados para higher order spectra

em WestminsterResearch - UK


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This paper examines the role of higher-order moments in portfolio choice within an expected-utility framework. We consider two-, three-, four- and five-parameter density functions for portfolio returns and derive exact conditions under which investors would all be optimally plungers rather than diversifiers. Through comparative statics we show the importance of higher-order risk preference properties, such as riskiness, prudence and temperance, in determining plunging behaviour. Empirical estimates for the S&P500 provide evidence for the optimality of diversification.

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This paper examines the effects of higher-order risk attitudes and statistical moments on the optimal allocation of risky assets within the standard portfolio choice model. We derive the expressions for the optimal proportion of wealth invested in the risky asset to show they are functions of portfolio returns third- and fourth-order moments as well as on the investor’s risk preferences of prudence and temperance. We illustrate the relative importance that the introduction of those higher-order effects have in the decision of expected utility maximizers using data for the US.

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This paper presents an ultra compact waveguide bandpass filter that exhibits a pseudo-elliptic response. The transmission zero created in the upper stopband to form a rapid roll off is produced through a bypass coupling with higher order modes. A 3rd order filter is designed at the centre frequency of 9.4 GHz with a 5.3% fractional bandwidth. The proposed structure's size is 38% smaller than one of a 3rd order E-plane extracted pole filter with comparable response. Additionally, this configuration allows larger span of different bandwidths. The filter has been fabricated and tested using E-plane waveguide technology, which has benefits of being inexpensive and having mass producible capabilities. Measurements of such a fabricated filter validate the simulated results.

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Much debate in schizotypal research has centred on the factor structure of the Schizotypal Personality Questionnaire (SPQ), with research variously showing higher-order dimensionality consisting of two to seven dimensions. In addition, cross-cultural support for the stability of those factors remains limited. Here, we examined the factor structure of the SPQ among British and Trinidadian adults. Participants from a White British sub-sample (n = 351) resident in the UK and from an African Caribbean sub-sample (n = 284) resident in Trinidad completed the SPQ. The higher-order factor structure of the SPQ was analysed through confirmatory factor analysis, followed by multiple-group analysis for the model of best-fit. Between-group differences for sex and ethnicity were investigated using multivariate analysis of variance in relation to the higher-order domains. The model of best-fit was the four-factor structure, which demonstrated measurement invariance across groups. Additionally, these data had an adequate fit for two alternative models: a) 3 factors and b) a modified 4-factor. The British sub-sample had significantly higher scores across all domains than the Trinidadian group, and men scored significantly higher on the disorganised domain than women. The four-factor structure received confirmatory support and, importantly, support for use with populations varying in ethnicity and culture.

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Tracing children’s values and value-expressive behavior over a sixth-month period, we examined stability and change of values and behavior and the reciprocal relations between them. Three hundred and ten sixth-grade students in Italy completed value and value-expressive behavior questionnaires three times in three-month intervals during the scholastic year. We assessed Schwartz's (1992) higher-order values of conservation, openness to change, self-enhancement, and self-transcendence, as well as their respective expressive behaviors. Reciprocal relations over time between values and behaviors were examined using a cross-lagged longitudinal design. Results showed that values and behaviors had reciprocal longitudinal effects on one another, after the stability of the variables was taken into account (i.e., values predicted change in behaviors, but also behaviors predicted change in values). Our findings also revealed that: (1) values were more stable over time than behaviors, and (2) the longitudinal effect of values on behaviors tended to be stronger than the longitudinal effect of behaviors on values. Findings are discussed in light of the recent developmental literature on value change.

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Ashton and colleagues concede in their response (Ashton, Lee, & Visser, in this issue), that neuroimaging methods provide a relatively unambiguous measure of the levels to which cognitive tasks co-recruit dif- ferent functional brain networks (task mixing). It is also evident from their response that they now accept that task mixing differs from the blended models of the classic literature. However, they still have not grasped how the neuroimaging data can help to constrain models of the neural basis of higher order ‘g’. Specifically, they claim that our analyses are invalid as we assume that functional networks have uncorrelated capacities. They use the simple analogy of a set of exercises that recruit multiple muscle groups to varying extents and highlight the fact that individual differences in strength may correlate across muscle groups. Contrary to their claim, we did not assume in the original article (Hampshire, High- field, Parkin, & Owen, 2012) that functional networks had uncorrelated capacities; instead, the analyses were specifically designed to estimate the scale of those correlations, which we referred to as spatially ‘diffuse’ factors

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What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or ‘‘factors’’ reflect the functional organiza- tion of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demon- strate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor ‘‘g’’ is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these com- ponents of intelligence by dissociating them using questionnaire variables. We propose that intelli- gence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.